Abstract
Aluminium coatings and their characterization are of great interest in many fields of application, ranging from aircraft industries to microelectronics. Here, we present the simulation of acoustic wave propagation in aluminium coatings via the elastodynamic finite integration technique (EFIT) in comparison to experimental results. The simulations of intensity (I)–defocus (z) curves, obtained by scanning acoustic microscopy (SAM), were first carried out on an aluminium bulk sample, and secondly on a 1 µm aluminium coating deposited on a silicon substrate. The I(z) curves were used to determine the Rayleigh wave velocity of the aluminium bulk sample and the aluminium coating. The results of the simulations with respect to the Rayleigh velocity were corroborated by non-destructive SAM measurements and laser ultrasonic measurements (LUS).
Highlights
Aluminium coatings offer a variety of favourable properties, including high reflectivity, high conductivity, high corrosion resistance, and low costs
scanning acoustic microscopy (SAM) represents a well-established tool in state-of-the-art failure and material characterization, providing high potential regarding automation [9], allowing fast and accurate failure detection
The aluminium layer was deposited via physical vapour deposition, 2 segment of an aluminium‐coated silicon wafer with (100)
Summary
Aluminium coatings offer a variety of favourable properties, including high reflectivity, high conductivity, high corrosion resistance, and low costs. The benefits of aluminium coatings render them attractive candidates for large-scale applications in aircraft industries, and for implementation in small-scale devices, concerning micro- and nano-electronics [1]. Some state-of-the-art methods show drawbacks concerning thin film characterization;. Ultrasonic waves can be used in order to determine thin film properties; e.g., via laser-induced ultrasound (LUS) [3,4,5,6] or via scanning acoustic microscopy (SAM) [7,8]. SAM represents a well-established tool in state-of-the-art failure and material characterization, providing high potential regarding automation [9], allowing fast and accurate failure detection
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
